The role of prosocial and proactive safety behaviors in predicting safety performance

© 2015 Elsevier Ltd. Employees' engagement in safety is assumed to be a significant contributor to safety performance within the chemical industry. The current study tested this assumption by examining the role of prosocial safety behaviors (e.g., helping others) and proactive safety behaviors (e.g., seeking change) in predicting four safety performance outcomes: micro-accidents, property damage (accidents without injury), near-miss events, and lost-time injuries. Two-wave data collected from 511 employees located in 2 Italian chemical plants revealed that prosocial safety behaviors predicted micro-accidents and property damage, and proactive safety behaviors predicted near-miss events and lost-time injuries. These results suggest that benefits can be gained from distinguishing between prosocial and proactive safety behaviors when seeking to improve safety performance. Organizations may reduce the rate of minor injuries and property damage by increasing helping among employees. However, this approach will be less effective in reducing more serious accidents or increasing near-miss event reporting. More effective in these cases is creating environments in which employees feel able to raise their suggestions and concerns about safety

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability